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Found 307 Skills
Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. Automatically detects file type and generates detailed markdown reports with format-specific analysis, quality metrics, and downstream analysis recommendations. Covers chemistry, bioinformatics, microscopy, spectroscopy, proteomics, metabolomics, and general scientific data formats.
Pragmatic qualitative analysis for interview data in sociology research. Guides you through systematic coding, interpretation, and synthesis with quality checkpoints. Supports theory-informed (Track A) or data-first (Track B) approaches.
Extract quantities from BIM/CAD data for cost estimation. Group by type, level, zone. Generate QTO reports.
Databricks documentation reference via llms.txt index. Use when other skills do not cover a topic, looking up unfamiliar Databricks features, or needing authoritative docs on APIs, configurations, or platform capabilities.
Design data systems by understanding storage engines, replication, partitioning, transactions, and consistency models. Use when the user mentions "database choice", "replication lag", "partitioning strategy", "consistency vs availability", or "stream processing". Covers data models, batch/stream processing, and distributed consensus. For system design, see system-design. For resilience, see release-it.
Deep-dive into analyst estimates and revision trends for any stock using Yahoo Finance data. Use when the user wants to understand analyst estimate direction, how EPS or revenue forecasts changed over time, compare estimate distributions, or analyze growth projections across periods. Triggers: "estimate analysis for AAPL", "analyst estimate trends for NVDA", "EPS revisions for TSLA", "how have estimates changed for MSFT", "estimate revisions", "EPS trend", "revenue estimates", "consensus changes", "analyst estimates", "estimate distribution", "growth estimates for", "estimate momentum", "revision trend", "forward estimates", "next quarter estimates", "annual estimates", "estimate spread", "bull vs bear estimates", "estimate range", or any request about tracking or comparing analyst estimates/revisions. Use this skill when the user asks about estimates beyond a simple lookup — if they want context, trends, or analysis, this is the right skill.
Analyze stock liquidity using bid-ask spreads, volume profiles, order book depth, market impact estimates, and turnover ratios via Yahoo Finance data. Use this skill whenever the user asks about liquidity, trading costs, bid-ask spread, market depth, volume analysis, slippage, market impact, turnover ratio, or how easy/hard it is to trade a stock without moving the price. Triggers: "how liquid is AAPL", "bid-ask spread", "volume analysis", "order book depth", "market impact of a large order", "turnover ratio", "slippage estimate", "can I trade 100k shares without moving the price", "liquidity comparison", "spread analysis", "ADTV", "Amihud illiquidity", "dollar volume", "execution cost estimate", "liquidity score", penny stocks, small caps, or thinly traded securities.
Use Crawl4AI for web crawling, markdown extraction, and LLM-powered structured extraction through OpenRouter. Use when the user mentions Crawl4AI, unclecode/crawl4ai, wants website data extracted with Crawl4AI, or needs an agent to crawl pages and turn them into structured JSON with OpenRouter-backed models.
Apache Spark distributed computing. Use for big data processing.
Process Excel files, supporting reading, analysis, statistics and export of xlsx data
This skill should be used when building data processing pipelines with CocoIndex v1, a Python library for incremental data transformation. Use when the task involves processing files/data into databases, creating vector embeddings, building knowledge graphs, ETL workflows, or any data pipeline requiring automatic change detection and incremental updates. CocoIndex v1 is Python-native (supports any Python types), has no DSL, and is currently under pre-release (version 1.0.0a1 or later).
Set up real-time indicator computation on live WebSocket market data. Streams LTP/Quote/Depth and computes indicators in real-time with optional Plotly live charting.